Drivers of Regional Competitiveness in the Central European Countries
Imre Lengyel () and
János Rechnitzer ()
Transition Studies Review, 2013, vol. 20, issue 3, 421-435
Abstract:
The examination of regional competitiveness has become a research question of outstanding importance in the Central European post-socialist countries since joining the EU. In our study we will proceed to analyse the competitiveness of 93 NUTS2 level regions of 8 Central European countries with the help of an empirical data base, using multivariable statistical methods. After introducing the database, we are going to investigate into the common revealed competitiveness indicator. Not only revealed competitiveness categories shall be analysed with the help of multivariable statistical procedures, but also the background processes described by the factor analysis and the multivariable linear regression model. Copyright CEEUN 2013
Keywords: Regional competitiveness; Pyramidal model; Drivers of competitiveness; Multivariable linear regression model; C10; O18; R10 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://hdl.handle.net/10.1007/s11300-013-0294-2 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:trstrv:v:20:y:2013:i:3:p:421-435
Ordering information: This journal article can be ordered from
http://www.springer. ... ration/journal/11300
DOI: 10.1007/s11300-013-0294-2
Access Statistics for this article
Transition Studies Review is currently edited by G. Dominese
More articles in Transition Studies Review from Springer, Central Eastern European University Network (CEEUN)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().